Enhancing Ergonomic Design Process with Digital Human Models for Improved Driver Comfort in Space Environment

Abstract

The primary focus of this research is to develop digital human models (DHM) that include accurate posture and motion prediction models for a diverse population. The posture and motion prediction models currently employed in DHMs must be adapted and improved based on actual motion data in order to provide validity for simulations of challenging dynamic activities (Ahmed et al. 2018). Additionally, if accurate models for predicting human posture and motion are developed and applied, they can be combined with psychophysical and biomechanical models to provide a deeper understanding of dynamic human performance and population-specific limitations, and these new DHM models will eventually serve as a useful tool for ergonomics design. In this line, we are making an effort to forecast driver comfort and postures when designing a mars rover's seat and peripherals using RAMSIS software. The core of RAMSIS is a highly accurate three-dimensional human model that is built on anthropometry databases from around the globe and can simulate humans with a variety of body measurements. To assess comfort during the design process, we employ a variety of additional analysis techniques, including those for comfort studies, eyesight, reachability, and force.